This is a startup post to get your dev environment setup for diving into Deep Learning. I have chosen to begin with TensorFlow and Keras for this task. I would be using the Jupyter notebook for demonstrating the dev setup.

Note: Jupyter itself is self sufficient for this task,
but I am using PyCharm for this task just to test the interoperability of PyCharm
with other ecosystem stack.

Create a new project with virtual env

Create a new Pure Python project in PyCharm and provide the settings for a virtual env. Pre-requisites for this step are python and virtual env. Make sure you have these steps before creation of new project:

Install Python

Install pip

Install virtualenv (pip install virtualenv)

PyCharm settings for new project. Make sure you chose python 3.6 for the virtual env :

Activate the virtual env if not already activated:

Open the terminal from PyCharm

Activate virtualenv :

$> source venv/bin/activate

Terminal command:

Install all python requirements for our project

Create a requirements.txt file in the project and add the python dependencies in it.